Bancassurance (i.e., banca + assurance) refers to the provision and selling of
both banking and insurance products by one organization to the same client-base.
Bancassurance takes several structural forms (Saunders & Walter,1994):
Full integration – Risk is shared between the parties (minimal A.S or M.H)
Mergers and acquisitions (M&A) – Risk sharing, agency conflicts
Joint ventures (JV) – Conflicts resulting from poor integration and cooperation
Distribution agreements – No sharing of risk – (agency problems)
Study of M&As is anchored on:
• Neoclassical economic theory: e.g. efficiency theory of mergers
• Behavioural hypothesis: e.g. agency theory (agency problems).
3. Thesis Statement
• Between 1989-2002, governmental policies in the U.S. and U.K. encouraged massive
integration and conglomeration within the financial services industry. M&As between
banks & insurers created a dominant group of large - complex financial institutions
(LCFIs). – i.e. “Too Big to Fail”
• By 2007, 17 LCFIs controlled the markets for debt and equity underwriting.
▫ High risky activities
▫ Failure of the LCFIs incurred huge social costs.
• These M&As were the epicentre and the catalyst of the subprime mortgage crisis.
Three elements stand out:
▫ Do these structures create value or they consistently destroy their shareholder’s wealth?
▫ How reliable is corporate governance in putting checks & balances to cultivate sound
▫ Will the regulations be sufficient to avert any future crises? 5
Bancassurance vs Subprime Mortgage Crisis
4. Literature Review (1)
1. Risk-return profile:
(a) Elyasiani et al. (2016), Schneider (2014),
Nurullah & Staikouras (2008),
(b) Fields et al. (2007),
(c) Weiß et al. (2014).
(a) Risk diversification benefits
(b) No risk changes.
(c) Systemic risk.
2. Efficiency gains:
(a) Peng et al. (2017), Hwang & Gao (2005)
(b) Casu & Girardone (2004).
(a) Increase in profit efficiency for financial
(b) Higher cost efficiency for life insurance
3. Institutional Analysis
(a) Staikouras (2006), Brophy (2013), Artikis et al.(2008)
(a) JV is best model for selling these kinds
No direct evidence on welfare effects of bancassurance! 6
5. Literature Review (2)
Wealth effects of Bank-insurance M&A
1. Cybo-ottone & Murgia (2000)
(a) EU investment banking group 1988-1997.
(b) 10 bank-insurer deals
(a) Positive wealth effects for F. conglomerates.
(b) Insignificant ARs for bidders
→ No wealth changes
2. Fields at al. (2007a; b)
(a) Viability of bancassurance combinations for U.S.
and EU mergers between 1997-2002
(a) Didn’t differentiate between bank bids for
insurers and vice-versa.
→ (+ ve) wealth effects
3. Chen and Tan (2011).
(a) Risk and wealth effects of Bank-insurance for EU
(a) Focus is on bank’s value
→ (- ve) wealth effects
4. Staikouras (2009); Dontis-Charitos et al. (2011).
Stock market valuation of bank-insurance M&As
(a) US and Europe for the period 1990-2006.
(b) US, Europe, Canada and Australia 1990-2006
(a) Bank-bidders earn significant +ve ARs, while
the insurance-bidders significant losses.
(b) No-wealth changes for insurance bidders.
→ (+ve) wealth effects.
Less focus is on insurer’s value Limited/outdated dataset Conflicting results 7
6. Literature Review (3)
• Only one set of study (i.e. No.4) analysed both sides of the phenomenon, however, their
findings are still conflicting and based on a dataset of up 2006.
• My research aims to advance the existing literature by answering these questions:
▫ Does Bancassurance M&As create or destroy shareholder’s value in the affected firms?
▫ Does it alter the idiosyncratic risk of the firms & trigger additional market-wide risks?
▫ What are the specific factors that determine excess/AR?
• H1 : There is no significant announcement effect in ARs for acquirers and targets.
• H2 : Cross-industry M&A have no significant effect the risk of individual firms and that of the
entire financial system.
7. Contributions to Knowledge
1. M&A and shareholder’s wealth/value
• Impact of bancassurance on shareholder’s wealth from insurers’ viewpoint (little attention).
• The most comprehensive and up-to-date dataset spanning the period characterized
by 3 major economic depressions 1999-2019.
• Accounting returns for M&As in the context of bancassurance (poorly investigated).
2. Corporate governance
• New arguments on the impact of CG characteristics agency problems (adverse
selection and moral hazard) on M&A performance.
3.Capital adequacy regulation
• This will be the first study to link capital adequacy with M&As
→ How compliance or non-compliance to capital adequacy requirements impacts on
8. Methodology (1)
• Event-study approach by Brown and Warner (1985).
• Zephyr database to identify my initial sample (1999-2019)
• Daily stock prices of each firm and market indices
• Event timeline
▫ Estimation period = 200 days (-41, -240)
▫ Event window= 61 days (-30, +30)
• Sharpe (1963) market model (MM)
• To minimise the contamination in estimation window: GARCH-model (Bollerslev’, 1986)
𝑅𝑖,𝑡 = 𝛼𝑖 + 𝛽𝑖𝑅𝑚,𝑡 + 𝜀𝑖,𝑡
= ℎ𝑖,𝑡 = 𝛼 + 𝛽1𝜀𝑡−1
𝐴𝑅𝑖𝑡 = 𝑅𝑖,𝑡 − 𝐸 𝑅𝑖𝑡|∅𝑖𝑡
𝐶𝐴𝑅𝑡 = 𝑖=−30
(𝑎𝑖 + 𝛽𝑖𝑅𝑚𝑡)
9. Methodology (2)
• AAR and CAAR to measure the total impact of the event (M&A)
• Testing statistical significance of excess-returns with standard t-test.
• Iterating for deal characteristics, e.g. listing effect, domestic vs cross-boarder & method of payment.
• CARs as a dependent variable to conduct a correlation with profitability and synergy measures.
▫ Profitability proxies: E.g. bidder or target ROA
▫ Economies of scale: Relative size of target to bidder ( in terms of total assets and market value)
▫ Economies of scope: (Revenue, cost/expense and profitability). 11
𝑡 = 𝐴𝐴𝑅𝑡
𝑁2 𝑇 − 1
𝐶𝐴𝐴𝑅𝑇 = 𝑖=1
12. Discussion and Conclusion (1)
• During the pre-announcement period:
▫ There is an alternating pattern of +ve and –ve returns in equal proportions
▫ None of these are significant
▫ No event anticipation or leakage of information prior to M&A announcements
• The CAAR for the entire sample at day (0) = 0.27%, with t-stat =1.67.
▫ It is positive and significant (at 10% level)
▫ There is (+ ve) wealth effects
• The CAAR for the entire sample is also +ve and significant at day 4, 5 and 6 (Jumps)
▫ This could be driven mainly by bank-bidder deals
▫ This delay in the market reaction could be attributed to different market efficiencies
• The CAAR for bank bidders at day (0) = 0.36%, with t-stat=1.98, while day (1) = -0.32%, 1.78
▫ The +ve returns show that investors are optimistic – M&A would be beneficial
▫ The –ve returns signify that investors over-reacted initially & the situation quickly corrected
13. Discussion and Conclusion (2)
• In table 2: CAAR of the entire sample is significant at windows:
▫ (-5, +5) =1.06%, with t-stat =1.98 (10%-level)
▫ (0, +2) = 0.29%, with t-stat = 3.16 (5%-level)
▫ This still confirm that bancassurance generate (+ ve) wealth effects
• Bank-bidders exhibit +ve and significant ARs only in one window:
▫ (-5, +5) =1.17%, with t-stat =1.97 (10%-level)
• Interestingly insurance-bidders revealed insignificant ARs throughout
• Results are comparable to Dontis-Charitos et al. (2011)
▫ Significant abnormal returns for bank bidders
▫ Insignificant excess returns for insurance bidders.